Jose Dolz
Orcid: 0000-0002-2436-7750
According to our database1,
Jose Dolz
authored at least 100 papers
between 2014 and 2024.
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Bibliography
2024
Medical Image Anal., January, 2024
Medical Image Anal., January, 2024
CoRR, 2024
2023
Medical Image Anal., 2023
Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.
Medical Image Anal., 2023
A Foundation LAnguage-Image model of the Retina (FLAIR): Encoding expert knowledge in text supervision.
CoRR, 2023
CoRR, 2023
Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic Segmentation.
CoRR, 2023
Proceedings of the Medical Imaging with Deep Learning, 2023
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Maximum Entropy on Erroneous Predictions: Improving Model Calibration for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the Information Processing in Medical Imaging, 2023
Proceedings of the Information Processing in Medical Imaging, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Exploring the Transferability of a Foundation Model for Fundus Images: Application to Hypertensive Retinopathy.
Proceedings of the Advances in Computer Graphics, 2023
2022
Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty.
IEEE Trans. Medical Imaging, 2022
IEEE J. Biomed. Health Informatics, 2022
Incremental multi-target domain adaptation for object detection with efficient domain transfer.
Pattern Recognit., 2022
Medical Image Anal., 2022
Leveraging Uncertainty for Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images.
CoRR, 2022
On the Pitfalls of Entropy-Based Uncertainty for Multi-class Semi-supervised Segmentation.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2022
Leveraging Labeling Representations in Uncertainty-Based Semi-supervised Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the 30th European Signal Processing Conference, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images.
IEEE Trans. Medical Imaging, 2021
IEEE Trans. Medical Imaging, 2021
IEEE J. Biomed. Health Informatics, 2021
IEEE J. Biomed. Health Informatics, 2021
Knowledge distillation methods for efficient unsupervised adaptation across multiple domains.
Image Vis. Comput., 2021
Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation.
CoRR, 2021
CoRR, 2021
Bladder segmentation based on deep learning approaches: current limitations and lessons.
CoRR, 2021
MRI and CT bladder segmentation from classical to deep learning based approaches: Current limitations and lessons.
Comput. Biol. Medicine, 2021
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the Information Processing in Medical Imaging, 2021
Proceedings of the 29th European Signal Processing Conference, 2021
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Proceedings of the 32nd British Machine Vision Conference 2021, 2021
Proceedings of the 32nd British Machine Vision Conference 2021, 2021
2020
Neural Networks, 2020
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models.
CoRR, 2020
Comput. Medical Imaging Graph., 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge.
IEEE Trans. Medical Imaging, 2019
IEEE Trans. Medical Imaging, 2019
CoRR, 2019
Deep weakly-supervised learning methods for classification and localization in histology images: a survey.
CoRR, 2019
Weakly Supervised Object Localization using Min-Max Entropy: an Interpretable Framework.
CoRR, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
2018
3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.
NeuroImage, 2018
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.
NeuroImage, 2018
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning.
CoRR, 2018
Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks.
CoRR, 2018
IVD-Net: Intervertebral Disc Localization and Segmentation in MRI with a Multi-modal UNet.
Proceedings of the Computational Methods and Clinical Applications for Spine Imaging, 2018
Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
Isointense infant brain segmentation with a hyper-dense connected convolutional neural network.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Proceedings of the 2018 on International Conference on Multimodal Interaction, 2018
2017
HyperDense-Net: A hyper-densely connected CNN for multi-modal image semantic segmentation.
CoRR, 2017
A 3D fully convolutional neural network and a random walker to segment the esophagus in CT.
CoRR, 2017
A deep learning classification scheme based on augmented-enhanced features to segment organs at risk on the optic region in brain cancer patients.
CoRR, 2017
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017
2016
User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy.
J. Digit. Imaging, 2016
Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study.
Comput. Medical Imaging Graph., 2016
Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.
Int. J. Comput. Assist. Radiol. Surg., 2016
2015
A fast and fully automated approach to segment optic nerves on MRI and its application to radiosurgery.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015
2014
Combining watershed and graph cuts methods to segment organs at risk in radiotherapy.
Proceedings of the Medical Imaging 2014: Image Processing, 2014
Proceedings of the Medical Imaging 2014: Image Processing, 2014